About the true type of smoothers

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dc.creatorEzri, D.
dc.creatorBobrovsky, B. Z.
dc.creatorSchuss, Z.
dc.date2008-02-01
dc.date.accessioned2026-07-07T09:18:15Z
dc.date.available2026-07-07T09:18:15Z
dc.descriptionWe employ the variational formulation and the Euler-Lagrange equations to study the steady-state error in linear non-causal estimators (smoothers). We give a complete description of the steady-state error for inputs that are polynomial in time. We show that the steady-state error regime in a smoother is similar to that in a filter of double the type. This means that the steady-state error in the optimal smoother is significantly smaller than that in the Kalman filter. The results reveal a significant advantage of smoothing over filtering with respect to robustness to model uncertainty.
dc.descriptionNon-causal estimation
dc.identifierhttps://arxiv.org/abs/0802.0130
dc.identifierhttp://arxiv.org/abs/0802.0130
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/153960
dc.subjectOptimization and Control
dc.subjectInformation Theory
dc.subject60G35; 93E10; 94A05
dc.titleAbout the true type of smoothers
dc.typetext

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